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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2018.1
- 수록면
- 248 - 255 (8page)
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A noteworthy change in recent medical research is the rapid increase of research using big data obtained from electrical medical records (EMR), order communication systems (OCS), and picture archiving and communication systems (PACS). It is often difficult to apply traditional statistical techniques to research using big data because of the vastness of the data and complexity of the relationships. Therefore, the application of artificial intelligence (AI) techniques which can handle such problems is becoming popular. Classical machine learning techniques, such as k-means clustering, support vector machine, and decision tree are still efficient and useful for some research problems. The deep learning techniques, such as multi-layer perceptron, convolutional neural network, and recurrent neural network have been spotlighted by the success of deep belief networks and convolutional neural networks in solving various problems that are difficult to solve by conventional methods. The results of recent research using artificial intelligence techniques are comparable to human experts. This article introduces technologies that help researchers conduct medical research and understand previous literature in the era of AI.
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참고문헌 (44)
참고문헌 신청
Ehteshami Bejnordi B / 2017 / Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer / JAMA 318:2199~2210
Gulshan V / 2016 / Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs / JAMA 316:2402~2410
Esteva A / 2017 / Dermatologist-level classification of skin cancer with deep neural networks / Nature 542:115~118
Bickford RG / 1950 / Automatic electroencephalographic control of general anesthesia / Electroencephalogr Clin Neurophysiol 2:93~96
Pasin L / 2017 / Closed-loop delivery systems versus manually controlled administration of total IV anesthesia / Anesth Analg 124:456~464
Gulshan V / 2016 / Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs / JAMA 316:2402~2410
Esteva A / 2017 / Dermatologist-level classification of skin cancer with deep neural networks / Nature 542:115~118
Bickford RG / 1950 / Automatic electroencephalographic control of general anesthesia / Electroencephalogr Clin Neurophysiol 2:93~96
Pasin L / 2017 / Closed-loop delivery systems versus manually controlled administration of total IV anesthesia / Anesth Analg 124:456~464
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